TY - GEN
T1 - A novel perceptual feature set for audio emotion recognition
AU - Sezgin, Mehmet Cenk
AU - Gunsel, Bilge
AU - Kurt, Gunes Karabulut
PY - 2011
Y1 - 2011
N2 - We present a novel system for audio emotion recognition based on the Perceptual Evaluation of Audio Quality (PEAQ) model as described by the standard, ITU-R BS.13871 which provides a mathematical model resembling the human auditory system. The introduced feature set performs perceptual analysis in time, spectral and Bark domains thus enabling us to represent the statistics of emotional audio for arousal and valence modes with a small number of features. Unlike the existing systems, the proposed feature set learns statistical characteristic of emotional differences hence does not require data normalization to eliminate speaker or corpus dependency. Recognition performance obtained for the well known VAM and EMO-DB corpora show that the classification accuracy achieved by the proposed feature set outperforms the reported benchmarking results particularly for valence both for natural and acted emotional data.
AB - We present a novel system for audio emotion recognition based on the Perceptual Evaluation of Audio Quality (PEAQ) model as described by the standard, ITU-R BS.13871 which provides a mathematical model resembling the human auditory system. The introduced feature set performs perceptual analysis in time, spectral and Bark domains thus enabling us to represent the statistics of emotional audio for arousal and valence modes with a small number of features. Unlike the existing systems, the proposed feature set learns statistical characteristic of emotional differences hence does not require data normalization to eliminate speaker or corpus dependency. Recognition performance obtained for the well known VAM and EMO-DB corpora show that the classification accuracy achieved by the proposed feature set outperforms the reported benchmarking results particularly for valence both for natural and acted emotional data.
KW - emotion recognition
KW - PEAQ
KW - Perceptual audio feature extraction
UR - http://www.scopus.com/inward/record.url?scp=79958700362&partnerID=8YFLogxK
U2 - 10.1109/FG.2011.5771348
DO - 10.1109/FG.2011.5771348
M3 - Conference contribution
AN - SCOPUS:79958700362
SN - 9781424491407
T3 - 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
SP - 780
EP - 785
BT - 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
T2 - 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
Y2 - 21 March 2011 through 25 March 2011
ER -